The Development of Learning Skills and Outcome-Based Education in Political Science at Yasothon Buddhist College

Abstract

This research article aimed to: 1) examine the problems and essential needs related to developing learning capacity and implementing outcome-based teaching and learning in the field of Political Science; 2) develop an outcome-based learning manual for Political Science and apply it within the context of the College of Buddhist Studies, Yasothon; and 3) enhance students’ learning skills and competencies through outcome-based instructional practices in Political Science. A mixed-methods research design was employed. In the phase of investigating the current conditions and essential needs, the sample consisted of 306 participants, and 30 participants were selected for in-depth interviews. For the model development phase, five experts were invited to evaluate the proposed model. In the outcome assessment phase, 13 experts participated in a focus group discussion. For the model validation phase, 306 participants assessed user satisfaction. Simple random sampling was employed for selecting the sample and satisfaction evaluators, while key informants were purposively selected based on specific inclusion and exclusion criteria. Data analysis tools included percentage, mean, standard deviation, normality testing, the Modified Priority Needs Index (PNI _modified), factor analysis, and multiple regression analysis.

The research found that:

The findings revealed that seven observable variables-namely educational philosophy, educational administration, 21st-century education, outcome-based instruction, active learning models, educational measurement and evaluation, and educational quality assurance-significantly influenced outcome-based teaching and learning. The overall mean score was  = 3.16 with a standard deviation of 1.77, indicating a moderate level. Qualitative data also reflected a moderate overall trend. The correlation coefficients ranged from .400 to .526 and were statistically significant at the .01 level. The model explained 35.6% of the variance, with an error term of .347. All seven independent variables jointly served as effective predictors of the dependent variable.